To achieve more rapid throughput of tomographic processing, we have continued work on implementing tomographic reconstruction algorithmns on the massively parallel Intel Paragon computer at the San Diego Super Computer Center. The single axis tilt R-weighted backprojection algorithm can be parallelized since each plane of the volume orthogonal to the tilt axis may be processed separately on a node of the Paragon using an identical algorithm. However, the Fourier based methods, including R-weighted backprojection, may not achieve the maximum resolution possible from the tilt series data because it is difficult to incorporate other sources of information which constrain the nature of the specimen. These constraints include compact support, smoothness, and positivity of the mass density distribution. Therefore, we have been examining the use of iterative methods including the algebraic reconstruction (ART) and simultaneous interative reconstruction (SIRT) techniques which do employ this additional information. Generally, these procedures interatively correct the backprojected volume using an error measure derived by comparing projections from the volume against the corresponding tilt data images. We have implemented these iterative procedures on Macintosh computers and on our Unix workstations and, in agreement with reports from other laboratories, they appear to generate improved reconstructions relative to the backprojection procedure, at least for some specimens. These iterative methods require considerable computational time because they will often be performed after an initial R-weighted backprojection and many iterations may be required to achieve the optimum results. These algorithms are also well suited to parallelization. We have completed an initial implementation of the R-weighted backprojection and iterative methods on the Paragon. This version achieves a 2-3 times increase in speed compared to computation using a conventional method on a high performance SGI workstation. We expect to obtain further enhancement in performance after optimization of the program. We are also devel9ping an interface to the asynchronous communication environment we have developed for our telemicroscopy (CMDA) project to provide automatic transfer of data from the microscope, initiation of task execution on the Paragon, and return of the computed result over the network.